Description: 这是我从网上下载到的Locally Linear Embedding(LLE)的Matlab代码,希望对研究Manifold Leanring的同事有所帮助。-This is my downloaded from the Internet to the Locally Linear Embedding (Locally ) Matlab code, and I hope to study Manifold Leanring colleagues help. Platform: |
Size: 2969 |
Author:赵启军 |
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Description: 这是我从网上下载到的Locally Linear Embedding(LLE)的Matlab代码,希望对研究Manifold Leanring的同事有所帮助。-This is my downloaded from the Internet to the Locally Linear Embedding (Locally ) Matlab code, and I hope to study Manifold Leanring colleagues help. Platform: |
Size: 3072 |
Author:赵启军 |
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Description: 局部线性嵌入法,用于数据降维
.lle.m -- A simple matlab routine to perform LLE.
.scurve.m -- Code to run the "s-curve" example.
.swissroll.m -- Code to run the "swiss roll" example.
-Locally Linear Embedding method for data dimensionality reduction. Lle.m- A simple matlab routine to perform LLE.. Scurve.m- Code to run the s-curve example.. Swissroll.m- Code to run the swiss roll example. Platform: |
Size: 7168 |
Author:Mike |
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Description: Many problems in statistical pattern recognition begin with the preprocessing of multidimensional signals, such as images of faces or spectrograms of speech.
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Author:memcpy |
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Description: 这是LLE的原始算法,原文的参考文献是:S.T.Roweis and L.K.Saul. Nonlinear dimensionality reduction by locally linear embedding. Science,
290, 2000.-This is the original LLE algorithm, the original reference is: STRoweis and LKSaul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290, 2000. Platform: |
Size: 1024 |
Author:treat |
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Description: This toolbox is an educational and recreative toolbox around recent ideas in the field of dimension reduction.
* PCA : classical Principal Componnent Analysis (linear projection).
* Nonlinear dimensionality reduction by locally linear embedding.
* Laplacian Eigenmaps for dimensionality reduction and data representation-This toolbox is an educational and recreative toolbox around recent ideas in the field of dimension reduction.
* PCA : classical Principal Componnent Analysis (linear projection).
* Nonlinear dimensionality reduction by locally linear embedding.
* Laplacian Eigenmaps for dimensionality reduction and data representation Platform: |
Size: 226304 |
Author:tra ba huy |
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Description: 基于多帧图像插值(Interpolation)技术的方法是SR恢复技术当中最直观
的方法。这类方法首先估计各帧图像之间的相对运动信息,获得HR图像在非均
匀间距采样点上的象素值,接着通过非均匀插值得到HR栅格上的象素值,最后
采用图像恢复技术来去除模糊和降低噪声(运动估计!非均匀插值!去模糊和
噪声)。-In this paper, we propose a novel method for solv-
ing single-image super-resolution problems. Given a
low-resolution image as input, we recover its high-
resolution counterpart using a set of training exam-
ples. While this formulation resembles other learning-
based methods for super-resolution, our method has
been inspired by recent manifold learning methods, par-
ticularly locally linear embedding (LLE). Speci?cally,
small image patches in the low- and high-resolution
images form manifolds with similar local geometry in
two distinct feature spaces. As in LLE, local geometry
is characterized by how a feature vector correspond-
ing to a patch can be reconstructed by its neighbors
in the feature space. Besides using the training image
pairs to estimate the high-resolution embedding, we
also enforce local compatibility and smoothness con-
straints between patches in the target high-resolution
image through overlapping. Experiments show that our
method is very ?exible Platform: |
Size: 27595776 |
Author:qianyeyu |
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Description: Locally-Linear Embedding (LLE)[9] was presented at approximately the same time as Isomap. It has several advantages over Isomap, including faster optimization when implemented to take advantage of sparse matrix algorithms, and better results with many problems. LLE also begins by finding a set of the nearest neighbors of each point. It then computes a set of weights for each point that best describe the point as a linear combination of its neighbors. Finally, it uses an eigenvector-based optimization technique to find the low-dimensional embedding of points, such that each point is still described with the same linear combination of its neighbors. LLE tends to handle non-uniform sample densities poorly because there is no fixed unit to prevent the weights from drifting as various regions differ in sample densities. LLE has no internal model. Platform: |
Size: 2048 |
Author:Karthikeyan |
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Description: 基于流形的lle(局部线性嵌入)算法。 可以设置领域大小,计算速度较快。-Based on manifold lle (Locally Linear Embedding) algorithm. Field size can be set to calculate faster. Platform: |
Size: 1024 |
Author:陈普登 |
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Description: 基于LLE(局部线性嵌入)算法的瑞士卷降维程序,程序自动生成瑞士卷,然后降维输出图像。-Based on LLE (locally linear embedding) dimensionality reduction algorithm Swiss roll program, the program automatically generates Swiss roll, then drop-dimensional output image. Platform: |
Size: 1024 |
Author:陈普登 |
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Description: LLE(局部线性嵌入)算法研究介绍的pdf,属于算法的开山之作,LLE算法基础核心。学习LLE从这篇开始。-LLE (Locally Linear Embedding) algorithm introduced in pdf, the mountains are algorithms for, LLE algorithm is based on the core. LLE learn from this start. Platform: |
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Author:陈普登 |
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Description: 局部线性嵌入,是一种流行学习的算法,可以学习任意维数的低维流形-locally linear embedding is a algorithm of manifold learning, it can be used to learn arbitrary dimension of low dimensional manifold
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Author:QSJ |
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